In a projection video display, geometrical raster distortions result from the physical placement of the cathode ray display tubes. Such raster distortions are exacerbated by the use of cathode ray tubes with curved, concave display surfaces and the inherent magnification in the optical projection path. The projected image is composed of three scanning rasters which are required to be in register one with the other on a viewing screen. The precise overlay of the three projected images requires the adjustment of multiple waveforms to compensate for geometrical distortion and facilitate the superimposition of the three projected images. However, manual alignment of multiple waveforms is labor intensive during manufacturing, and without the use of sophisticated test equipment may preclude setup at a field or user location. Field adjustment is frequently required as a consequence of display relocation which changes the direction and intensity of the Earth's magnetic field incident on the display. Such geomagnetic fields and additional incidental magnetic fields from local magnetized objects introduce some display image rotation but mainly cause a rectilinear movement of the entire picture. Thus an automated convergence system is disclosed which simplifies manufacturing alignment and facilitates field location adjustment. An automated alignment system may employ raster edge measurement at peripheral screen locations in order to determine raster size and convergence. However, errors in the center screen region are not measured, since a center screen sensor is, for obvious reasons, undesirable. In a projection television receiver convergence of the 3 color images may be restored after the instrument has been moved to a different magnetic field using an array of 8 light sensors located around the edges of the picture so as to form a 3×3 matrix. The central sensor is missing. To store convergence, for each of the three colors, the sensors are first located after the initial convergence alignment using the high contrast edges of lighted areas that are fixed in position relative to the picture geometry. The picture is moved via digital convergence deflection. The digital value of said deflection corresponding to an edge location for each color and each sensor is stored in non volatile memory. When the receiver is moved to a new location geomagnetic field changes introduce rectilinear movement of the entire picture and some display image rotation. Because this image displacement is consistent over the whole image an average correction value can be computed for use at the screen center. Convergence is restored by again measuring the sensor locations. For each color a 3×3 difference matrix is calculated using the initial and recent sensor location data. Each color picture is then distorted by applying the 3×3 difference matrix result via parabolic curve fitting to the 15×13 digital convergence correction matrix that covers the same picture area. This process restores the initial relationship of the picture geometry to the sensor positions. Small convergence errors may remain at the screen center. These may be manually corrected by overlaying one color on another using a centered video display of the two colors having high contrast vertical and horizontal edges. A 3×3 difference matrix is then calculated for the color that has been manually moved using 0 error for all locations except the center and the manual movement distance for the center error. For the color where the center was moved the picture is then distorted as described above. Progressive rounding errors and undesired convergence errors occur if this center adjustment is done multiple times without rerunning the sensor finding routine which erases any previous center correcting adjustment.